Affiliations: College of Information and Control Engineering, Jilin Institute of Chemical Technology, Jilin, China
Correspondence:
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Corresponding author. Long Qi, College of Information and Control Engineering, Jilin Institute of Chemical Technology, Jilin, China. E-mail: [email protected].
Abstract: In order to complete the loading operation in a short time, the genetic algorithm was improved, and the improved mechanisms such as the total crossover of the population and the distributed dynamic penalty function method were proposed. The distribution of ballast water in barge stowage was optimized. The calculation of the ship’s floating state, stability, the check of the program strength, and the improvement of the genetic algorithm were discussed. By simplifying the model, all ballast water tanks were involved in the stowage, so as to better meet the limitation of tide level, tank capacity and strength. A more adaptable load optimization solution was obtained. The results show that the improved genetic algorithm has shorter time and higher efficiency than the basic loading scheme. The improved genetic algorithm was used to optimize the barge loading plan, which met the engineering requirements and shorten the working time of the barge. Therefore, the research on the improved genetic algorithm can effectively improve the quality and reliability of the project, which is beneficial to improve the scientific, safety and reliability of the barge loading operation. This program has important implications for marine engineering.
